1. Field of the Invention
The present invention relates to an image processing apparatus and method which detect a feature point or perform feature point matching.
2. Description of the Related Art
Conventionally, there are varieties of technologies for detecting matching points among a plurality of images. As these kinds of technologies, the following technologies are famous. For example, a Harris corner detector (C. Harris and M. Stephens, “A combined corner and edge detector”, Proceedings of Fourth Alvey Vision Conference, 147-151, 1988) is a technology for detecting a feature point from an image. A SIFT (D. G. Lowe, “Object recognition from local scale-invariant features”, Proceedings of IEEE International Conference on Computer Vision (ICCV), 1150-1157, 1999) is a technology for detecting and matching a feature point.
Typically, a matching point is calculated through the following processing flow.
Feature point detection: feature points of two images are detected.
Feature quantity calculation: feature quantities at feature points of two images are calculated.
Matching point calculation: a matching point is detected from the matching degree of feature points between two images.
The number and distribution of matching points which are finally detected are significantly affected by detection sensitivity for feature points in the feature point detection or detection sensitivity in the matching point detection. As the detection sensitivity for feature points is increased, the number of feature points increases. However, the increase of the detection sensitivity raises the possibility that noise points which are not suitable as feature points will be detected as feature points. Furthermore, as the sensitivity of the matching point detection is increased, the number of feature points increases. However, the increase in sensitivity of the matching point detection raises the possibility that mismatch between feature points will occur. The sensitivities may include various sensitivities which are empirically obtained in consideration of parameters such as the desired numbers of feature points and matching points, an allowable ratio of noise points, and calculation time.
In an image composition technology using feature point matching between images or a technology for estimating a camera attitude change between images, it is desirable that matching points should be calculated in order to be uniformly distributed on the entire image. However, when the detection sensitivity for feature points or the detection sensitivity for matching points is constant, an excessively large or small number of matching points may exist in the image region.
As a technology for uniformly distributing matching points, Jpn. Pat. Appin. KOKAI Publication No. 2011-13890 discloses an image composition device and method which performs matching between two images, divides the image into a plurality of regions, and reduces matching points in each of the regions when the number of matching points within the region is large. Furthermore, Jpn. Pat. Appin. KOKAI Publication No. 2012-43403 discloses a feature point extraction method and device which changes detection sensitivity for feature points based on the value of pixel dispersion in a region, and adaptively detects feature points according to the magnitude of contrast in the region.